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JDart: Portfolio Solving, Breadth-First Search and SMT-Lib Strings (Competition Contribution)

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2021) 12652 LNCS 448-452
DOI: 10.1007/978-3-030-72013-1_30
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Abstract

JDart performs dynamic symbolic execution of Java programs: it executes programs with concrete inputs while recording symbolic constraints on executed program paths. A portfolio of constraint solvers is then used for generating new concrete values from recorded constraints that drive execution along previously unexplored paths. For SV-COMP 2021, we improved JDart by implementing exploration strategies, bounded analysis, and path-specific constraint solving strategies, as well as by enabling the use of SMT-Lib string theory for encoding of string operations.

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Mues, M., & Howar, F. (2021). JDart: Portfolio Solving, Breadth-First Search and SMT-Lib Strings (Competition Contribution). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12652 LNCS, pp. 448–452). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-72013-1_30

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